Results 41 to 50 of about 5,701,088 (332)
Application of a naive Bayesians classifiers in assessing the supplier [PDF]
Trendovi u Poslovanju, 2017 The paper considers the class of interactive knowledge based systems whose main purpose of making proposals and assisting customers in making decisions. The mathematical model provides a set of examples of learning about the delivered series of outflows ...
Mijailović Snežana, Ilić Đorđe
doaj +1 more source
Approximating Predictive Probabilities of Gibbs-Type Priors [PDF]
Sankhya A, 2020 Gibbs-type random probability measures, or Gibbs-type priors, are arguably the most "natural" generalization of the celebrated Dirichlet prior. Among them the two parameter Poisson-Dirichlet prior certainly stands out for the mathematical tractability and interpretability of its predictive probabilities, which made it the natural candidate in several ...
Arbel J., Favaro S.
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Bayesian analysis for the Lomax model using noninformative priors
Statistical Theory and Related Fields, 2023 The Lomax distribution is an important member in the distribution family. In this paper, we systematically develop an objective Bayesian analysis of data from a Lomax distribution. Noninformative priors, including probability matching priors, the maximal
Daojiang He, Dongchu Sun, Qing Zhu
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Learn and Tell: Learning Priors for Image Caption Generation
Applied Sciences, 2020 In this work, we propose a novel priors-based attention neural network (PANN) for image captioning, which aims at incorporating two kinds of priors, i.e., the probabilities being mentioned for local region proposals (PBM priors) and part-of-speech clues ...
Pei Liu, Dezhong Peng, Ming Zhang
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On predictive probability matching priors [PDF]
, 2008 We revisit the question of priors that achieve approximate matching of Bayesian and frequentist predictive probabilities. Such priors may be thought of as providing frequentist calibration of Bayesian prediction or simply as devices for producing frequentist prediction regions.
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Decision, probability, and utility: Prospect theory: An analysis of decision under risk
, 1979 A lubricator valve apparatus adapted for use when running wireline tools into an offshore well during a production test of the well. The valve includes a valve body having a central flow passage and a ball valve element for opening and closing the ...
D. Kahneman, A. Tversky
semanticscholar +1 more source
Optimal properties of some Bayesian inferences
, 2007 Relative surprise regions are shown to minimize, among Bayesian credible regions, the prior probability of covering a false value from the prior. Such regions are also shown to be unbiased in the sense that the prior probability of covering a false value
Evans, M., Shakhatreh, M.
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Bayesian priors for the eccentricity of transiting planets
, 2014 Planets on eccentric orbits have a higher geometric probability of transiting their host star. By application of Bayes' theorem, we reverse this logic to show that the eccentricity distribution of transiting planets is positively biased.
Kipping, David M.
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Getting the Measure of the Flatness Problem [PDF]
, 1995 The problem of estimating cosmological parameters such as $\Omega$ from noisy or incomplete data is an example of an inverse problem and, as such, generally requires a probablistic approach.
Coles P +8 more
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source